2 papers
cs.CV2026
Is Hierarchical Quantization Essential for Optimal Reconstruction?
Shirin Reyhanian, Laurenz Wiskott
Vector-quantized variational autoencoders (VQ-VAEs) are central to models that rely on high reconstruction fidelity, from neural compression to generative pipelines. Hierarchical e…
cs.CV2025
Understanding Transformer-based Vision Models through Inversion
Jan Rathjens, Shirin Reyhanian, David Kappel +1
Understanding the mechanisms underlying deep neural networks remains a fundamental challenge in machine learning and computer vision. One promising, yet only preliminarily explored…